Pandas Profiling Report

Dataset statistics

Number of variables	23
Number of observations	3664
Missing cells	6752
Missing cells (%)	8.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	2.2 MiB
Average record size in memory	631.8 B

Variable types

Categorical	13
Numeric	10

Alerts

`society` has a high cardinality: 674 distinct values	High cardinality
`sector` has a high cardinality: 115 distinct values	High cardinality
`areaWithType` has a high cardinality: 2349 distinct values	High cardinality
`price` is highly correlated with `price_per_sqft` and 7 other fields	High correlation
`price_per_sqft` is highly correlated with `price`	High correlation
`area` is highly correlated with `price` and 6 other fields	High correlation
`bedRoom` is highly correlated with `price` and 4 other fields	High correlation
`bathroom` is highly correlated with `price` and 5 other fields	High correlation
`super_built_up_area` is highly correlated with `price` and 6 other fields	High correlation
`built_up_area` is highly correlated with `price` and 3 other fields	High correlation
`carpet_area` is highly correlated with `price` and 5 other fields	High correlation
`servant room` is highly correlated with `price` and 3 other fields	High correlation
`price` is highly correlated with `bedRoom` and 2 other fields	High correlation
`area` is highly correlated with `super_built_up_area` and 2 other fields	High correlation
`bedRoom` is highly correlated with `price` and 2 other fields	High correlation
`bathroom` is highly correlated with `price` and 2 other fields	High correlation
`super_built_up_area` is highly correlated with `price` and 6 other fields	High correlation
`built_up_area` is highly correlated with `area` and 2 other fields	High correlation
`carpet_area` is highly correlated with `area` and 2 other fields	High correlation
`servant room` is highly correlated with `super_built_up_area`	High correlation
`price` is highly correlated with `price_per_sqft` and 4 other fields	High correlation
`price_per_sqft` is highly correlated with `price`	High correlation
`area` is highly correlated with `price` and 5 other fields	High correlation
`bedRoom` is highly correlated with `price` and 3 other fields	High correlation
`bathroom` is highly correlated with `price` and 5 other fields	High correlation
`super_built_up_area` is highly correlated with `price` and 6 other fields	High correlation
`built_up_area` is highly correlated with `area` and 2 other fields	High correlation
`carpet_area` is highly correlated with `area` and 3 other fields	High correlation
`servant room` is highly correlated with `bathroom` and 1 other fields	High correlation
`property_type` is highly correlated with `price` and 3 other fields	High correlation
`price` is highly correlated with `property_type` and 3 other fields	High correlation
`area` is highly correlated with `built_up_area` and 1 other fields	High correlation
`bedRoom` is highly correlated with `property_type` and 4 other fields	High correlation
`bathroom` is highly correlated with `property_type` and 5 other fields	High correlation
`balcony` is highly correlated with `bathroom`	High correlation
`floorNum` is highly correlated with `property_type`	High correlation
`super_built_up_area` is highly correlated with `price` and 3 other fields	High correlation
`built_up_area` is highly correlated with `area`	High correlation
`carpet_area` is highly correlated with `area`	High correlation
`servant room` is highly correlated with `bedRoom` and 2 other fields	High correlation
`facing` has 1042 (28.4%) missing values	Missing
`super_built_up_area` has 1788 (48.8%) missing values	Missing
`built_up_area` has 1988 (54.3%) missing values	Missing
`carpet_area` has 1793 (48.9%) missing values	Missing
`luxury_score` has 121 (3.3%) missing values	Missing
`area` is highly skewed (γ1 = 29.7471759)	Skewed
`built_up_area` is highly skewed (γ1 = 40.54726143)	Skewed
`carpet_area` is highly skewed (γ1 = 24.32687466)	Skewed
`floorNum` has 129 (3.5%) zeros	Zeros
`luxury_score` has 429 (11.7%) zeros	Zeros

Reproduction

Analysis started	2024-03-23 18:55:03.917080
Analysis finished	2024-03-23 18:55:15.839375
Duration	11.92 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

property_type
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	247.7 KiB

flat	2821
house	843

Length

Max length	5
Median length	4
Mean length	4.230076419
Min length	4

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	flat
2nd row	flat
3rd row	flat
4th row	flat
5th row	flat

Common Values

Value	Count	Frequency (%)
flat	2821	77.0%
house	843	23.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
flat	2821	77.0%
house	843	23.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

society
Categorical

HIGH CARDINALITY

Distinct	674
Distinct (%)	18.4%
Missing	1
Missing (%)	< 0.1%
Memory size	292.9 KiB

independent	481
tulip violet	75
ss the leaf	73
shapoorji pallonji joyville gurugram	42
dlf new town heights	42
Other values (669)	2950

Length

Max length	49
Median length	16
Mean length	16.87769588
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	307 ?
Unique (%)	8.4%

Sample

1st row	maa bhagwati residency
2nd row	apna enclave
3rd row	tulsiani easy in homes
4th row	smart world orchard
5th row	parkwood westend

Common Values

Value	Count	Frequency (%)
independent	481	13.1%
tulip violet	75	2.0%
ss the leaf	73	2.0%
shapoorji pallonji joyville gurugram	42	1.1%
dlf new town heights	42	1.1%
signature global park	35	1.0%
shree vardhman victoria	34	0.9%
smart world orchard	33	0.9%
emaar mgf emerald floors premier	32	0.9%
paras dews	31	0.8%
Other values (664)	2785	76.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
independent	486	5.0%
the	350	3.6%
dlf	219	2.3%
park	211	2.2%
city	163	1.7%
m3m	152	1.6%
global	152	1.6%
emaar	151	1.6%
signature	149	1.5%
heights	134	1.4%
Other values (783)	7482	77.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

sector
Categorical

HIGH CARDINALITY

Distinct	115
Distinct (%)	3.1%
Missing	0
Missing (%)	0.0%
Memory size	265.9 KiB

sohna road	154
sector 85	108
sector 102	106
sector 92	100
sector 69	93
Other values (110)	3103

Length

Max length	26
Median length	9
Mean length	9.31441048
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	sector 7
2nd row	sector 3
3rd row	sohna road
4th row	sector 61
5th row	sector 92

Common Values

Value	Count	Frequency (%)
sohna road	154	4.2%
sector 85	108	2.9%
sector 102	106	2.9%
sector 92	100	2.7%
sector 69	93	2.5%
sector 90	89	2.4%
sector 65	87	2.4%
sector 81	87	2.4%
sector 109	86	2.3%
sector 79	75	2.0%
Other values (105)	2679	73.1%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
sector	3436	46.7%
road	178	2.4%
sohna	166	2.3%
85	108	1.5%
102	106	1.4%
92	100	1.4%
69	93	1.3%
90	89	1.2%
65	87	1.2%
81	87	1.2%
Other values (107)	2904	39.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

price
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	473
Distinct (%)	12.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.533247817

Minimum	0.07
Maximum	31.5
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	57.2 KiB

Quantile statistics

Minimum	0.07
5-th percentile	0.37
Q1	0.95
median	1.525
Q3	2.75
95-th percentile	8.5
Maximum	31.5
Range	31.43
Interquartile range (IQR)	1.8

Descriptive statistics

Standard deviation	2.979057741
Coefficient of variation (CV)	1.175983542
Kurtosis	14.95329399
Mean	2.533247817
Median Absolute Deviation (MAD)	0.725
Skewness	3.281159259
Sum	9281.82
Variance	8.874785026
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1.25	80	2.2%
1.5	64	1.7%
1.2	64	1.7%
0.9	63	1.7%
1.1	62	1.7%
1.4	61	1.7%
1.3	57	1.6%
0.95	52	1.4%
2	52	1.4%
1.6	48	1.3%
Other values (463)	3061	83.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0.07	1	< 0.1%
0.16	1	< 0.1%
0.17	1	< 0.1%
0.19	1	< 0.1%
0.2	8	0.2%
0.21	6	0.2%
0.22	8	0.2%
0.23	1	< 0.1%
0.24	6	0.2%
0.25	11	0.3%

Value	Count	Frequency (%)
31.5	1	< 0.1%
27.5	1	< 0.1%
26	2	0.1%
25	1	< 0.1%
24	1	< 0.1%
23	1	< 0.1%
22	1	< 0.1%
20	3	0.1%
19.5	2	0.1%
19	3	0.1%

price_per_sqft
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct	2651
Distinct (%)	72.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	13895.28111

Minimum	4
Maximum	600000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	57.2 KiB

Quantile statistics

Minimum	4
5-th percentile	4716.15
Q1	6818
median	9022
Q3	13888.25
95-th percentile	33333
Maximum	600000
Range	599996
Interquartile range (IQR)	7070.25

Descriptive statistics

Standard deviation	23197.75796
Coefficient of variation (CV)	1.669470216
Kurtosis	187.1181187
Mean	13895.28111
Median Absolute Deviation (MAD)	2797.5
Skewness	11.44256221
Sum	50912310
Variance	538135974.4
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
10000	27	0.7%
8000	19	0.5%
5000	17	0.5%
12500	14	0.4%
11111	13	0.4%
6666	13	0.4%
22222	13	0.4%
8333	12	0.3%
7500	12	0.3%
6000	11	0.3%
Other values (2641)	3513	95.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
4	1	< 0.1%
5	1	< 0.1%
7	1	< 0.1%
9	1	< 0.1%
53	1	< 0.1%
57	1	< 0.1%
58	2	0.1%
60	1	< 0.1%
61	1	< 0.1%
79	1	< 0.1%

Value	Count	Frequency (%)
600000	1	< 0.1%
400000	1	< 0.1%
315789	1	< 0.1%
308333	1	< 0.1%
290948	1	< 0.1%
283333	1	< 0.1%
266666	1	< 0.1%
261194	1	< 0.1%
245398	1	< 0.1%
241666	1	< 0.1%

area
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED

Distinct	1312
Distinct (%)	35.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2886.718068

Minimum	50
Maximum	875000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	57.2 KiB

Quantile statistics

Minimum	50
5-th percentile	519
Q1	1232.25
median	1731.5
Q3	2300
95-th percentile	4244.35
Maximum	875000
Range	874950
Interquartile range (IQR)	1067.75

Descriptive statistics

Standard deviation	23154.90955
Coefficient of variation (CV)	8.021188423
Kurtosis	943.0595069
Mean	2886.718068
Median Absolute Deviation (MAD)	531.5
Skewness	29.7471759
Sum	10576935
Variance	536149836.1
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1650	54	1.5%
1350	48	1.3%
1800	47	1.3%
3240	43	1.2%
1950	43	1.2%
2700	39	1.1%
900	38	1.0%
2000	33	0.9%
2250	25	0.7%
2400	23	0.6%
Other values (1302)	3271	89.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
50	4	0.1%
55	1	< 0.1%
56	1	< 0.1%
57	1	< 0.1%
60	2	0.1%
61	1	< 0.1%
67	2	0.1%
70	1	< 0.1%
72	1	< 0.1%
76	1	< 0.1%

Value	Count	Frequency (%)
875000	1	< 0.1%
642857	1	< 0.1%
620000	1	< 0.1%
566667	1	< 0.1%
215517	1	< 0.1%
98978	1	< 0.1%
82781	1	< 0.1%
65517	2	0.1%
65261	1	< 0.1%
58228	1	< 0.1%

areaWithType
Categorical

HIGH CARDINALITY

Distinct	2349
Distinct (%)	64.1%
Missing	0
Missing (%)	0.0%
Memory size	426.8 KiB

Plot area 360(301.01 sq.m.)	36
Plot area 300(250.84 sq.m.)	26
Plot area 200(167.23 sq.m.)	19
Plot area 502(419.74 sq.m.)	18
Super Built up area 1950(181.16 sq.m.)Carpet area: 1161 sq.ft. (107.86 sq.m.)	17
Other values (2344)	3548

Length

Max length	124
Median length	38
Mean length	54.28848253
Min length	12

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1843 ?
Unique (%)	50.3%

Sample

1st row	Carpet area: 900 (83.61 sq.m.)
2nd row	Carpet area: 650 (60.39 sq.m.)
3rd row	Carpet area: 595 (55.28 sq.m.)
4th row	Carpet area: 1200 (111.48 sq.m.)
5th row	Super Built up area 1345(124.95 sq.m.)

Common Values

Value	Count	Frequency (%)
Plot area 360(301.01 sq.m.)	36	1.0%
Plot area 300(250.84 sq.m.)	26	0.7%
Plot area 200(167.23 sq.m.)	19	0.5%
Plot area 502(419.74 sq.m.)	18	0.5%
Super Built up area 1950(181.16 sq.m.)Carpet area: 1161 sq.ft. (107.86 sq.m.)	17	0.5%
Super Built up area 1578(146.6 sq.m.)	17	0.5%
Plot area 270(225.75 sq.m.)	16	0.4%
Super Built up area 1350(125.42 sq.m.)	15	0.4%
Super Built up area 1650(153.29 sq.m.)Carpet area: 1022.58 sq.ft. (95 sq.m.)	14	0.4%
Super Built up area 2010(186.74 sq.m.)	14	0.4%
Other values (2339)	3472	94.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
area	5556	18.5%
sq.m	3642	12.1%
up	3018	10.0%
built	2317	7.7%
super	1876	6.2%
sq.ft	1752	5.8%
sq.m.)carpet	1184	3.9%
sq.m.)built	699	2.3%
carpet	683	2.3%
plot	667	2.2%
Other values (2840)	8674	28.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

bedRoom
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	19
Distinct (%)	0.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.347434498

Minimum	1
Maximum	21
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	57.2 KiB

Quantile statistics

Minimum	1
5-th percentile	2
Q1	2
median	3
Q3	4
95-th percentile	6
Maximum	21
Range	20
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	1.879143679
Coefficient of variation (CV)	0.5613683197
Kurtosis	18.52566211
Mean	3.347434498
Median Absolute Deviation (MAD)	1
Skewness	3.502396113
Sum	12265
Variance	3.531180968
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=19)

Value	Count	Frequency (%)
3	1499	40.9%
2	941	25.7%
4	659	18.0%
5	200	5.5%
1	124	3.4%
6	73	2.0%
9	40	1.1%
8	30	0.8%
7	28	0.8%
12	27	0.7%
Other values (9)	43	1.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	124	3.4%
2	941	25.7%
3	1499	40.9%
4	659	18.0%
5	200	5.5%
6	73	2.0%
7	28	0.8%
8	30	0.8%
9	40	1.1%
10	20	0.5%

Value	Count	Frequency (%)
21	1	< 0.1%
20	1	< 0.1%
19	2	0.1%
18	2	0.1%
16	11	0.3%
14	1	< 0.1%
13	4	0.1%
12	27	0.7%
11	1	< 0.1%
10	20	0.5%

bathroom
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	19
Distinct (%)	0.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.41239083

Minimum	1
Maximum	21
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	57.2 KiB

Quantile statistics

Minimum	1
5-th percentile	2
Q1	2
median	3
Q3	4
95-th percentile	6
Maximum	21
Range	20
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	1.928271315
Coefficient of variation (CV)	0.5650792688
Kurtosis	17.92003729
Mean	3.41239083
Median Absolute Deviation (MAD)	1
Skewness	3.26707989
Sum	12503
Variance	3.718230264
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=19)

Value	Count	Frequency (%)
3	1079	29.4%
2	1046	28.5%
4	818	22.3%
5	289	7.9%
1	155	4.2%
6	117	3.2%
9	40	1.1%
7	38	1.0%
8	24	0.7%
12	21	0.6%
Other values (9)	37	1.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	155	4.2%
2	1046	28.5%
3	1079	29.4%
4	818	22.3%
5	289	7.9%
6	117	3.2%
7	38	1.0%
8	24	0.7%
9	40	1.1%
10	9	0.2%

Value	Count	Frequency (%)
21	1	< 0.1%
20	3	0.1%
18	4	0.1%
17	3	0.1%
16	7	0.2%
14	2	0.1%
13	4	0.1%
12	21	0.6%
11	4	0.1%
10	9	0.2%

balcony
Categorical

HIGH CORRELATION

Distinct	5
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	237.3 KiB

3+	1161
3	1074
2	884
1	364
0	181

Length

Max length	2
Median length	1
Mean length	1.316866812
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	3
4th row	2
5th row	3

Common Values

Value	Count	Frequency (%)
3+	1161	31.7%
3	1074	29.3%
2	884	24.1%
1	364	9.9%
0	181	4.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
3	2235	61.0%
2	884	24.1%
1	364	9.9%
0	181	4.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

floorNum
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	43
Distinct (%)	1.2%
Missing	19
Missing (%)	0.5%
Infinite	0
Infinite (%)	0.0%
Mean	6.815363512

Minimum	0
Maximum	51
Zeros	129
Zeros (%)	3.5%
Negative	0
Negative (%)	0.0%
Memory size	57.2 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	2
median	5
Q3	10
95-th percentile	18
Maximum	51
Range	51
Interquartile range (IQR)	8

Descriptive statistics

Standard deviation	6.02402662
Coefficient of variation (CV)	0.8838892613
Kurtosis	4.478673001
Mean	6.815363512
Median Absolute Deviation (MAD)	3
Skewness	1.687804208
Sum	24842
Variance	36.28889672
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=43)

Value	Count	Frequency (%)
3	493	13.5%
2	490	13.4%
1	350	9.6%
4	312	8.5%
8	195	5.3%
6	183	5.0%
10	179	4.9%
7	176	4.8%
5	169	4.6%
9	161	4.4%
Other values (33)	937	25.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	129	3.5%
1	350	9.6%
2	490	13.4%
3	493	13.5%
4	312	8.5%
5	169	4.6%
6	183	5.0%
7	176	4.8%
8	195	5.3%
9	161	4.4%

Value	Count	Frequency (%)
51	1	< 0.1%
45	1	< 0.1%
44	1	< 0.1%
43	2	0.1%
40	1	< 0.1%
39	2	0.1%
38	1	< 0.1%
35	2	0.1%
34	2	0.1%
33	4	0.1%

facing
Categorical

MISSING

Distinct	8
Distinct (%)	0.3%
Missing	1042
Missing (%)	28.4%
Memory size	224.6 KiB

East	621
North-East	621
North	386
West	247
South	231
Other values (3)	516

Length

Max length	10
Median length	5
Mean length	6.837147216
Min length	4

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	West
2nd row	West
3rd row	North-East
4th row	South-East
5th row	North-East

Common Values

Value	Count	Frequency (%)
East	621	16.9%
North-East	621	16.9%
North	386	10.5%
West	247	6.7%
South	231	6.3%
North-West	192	5.2%
South-East	171	4.7%
South-West	153	4.2%
(Missing)	1042	28.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
east	621	23.7%
north-east	621	23.7%
north	386	14.7%
west	247	9.4%
south	231	8.8%
north-west	192	7.3%
south-east	171	6.5%
south-west	153	5.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

agePossession
Categorical

Distinct	6
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	279.2 KiB

Relatively New	1640
New Property	591
Moderately Old	558
Undefined	447
Old Property	302

Length

Max length	18
Median length	14
Mean length	13.04012009
Min length	9

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Relatively New
2nd row	Old Property
3rd row	New Property
4th row	Undefined
5th row	Under Construction

Common Values

Value	Count	Frequency (%)
Relatively New	1640	44.8%
New Property	591	16.1%
Moderately Old	558	15.2%
Undefined	447	12.2%
Old Property	302	8.2%
Under Construction	126	3.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
new	2231	32.4%
relatively	1640	23.8%
property	893	13.0%
old	860	12.5%
moderately	558	8.1%
undefined	447	6.5%
under	126	1.8%
construction	126	1.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

super_built_up_area
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	593
Distinct (%)	31.6%
Missing	1788
Missing (%)	48.8%
Infinite	0
Infinite (%)	0.0%
Mean	1924.557862

Minimum	89
Maximum	10000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	57.2 KiB

Quantile statistics

Minimum	89
5-th percentile	762.75
Q1	1478.75
median	1828
Q3	2215
95-th percentile	3185
Maximum	10000
Range	9911
Interquartile range (IQR)	736.25

Descriptive statistics

Standard deviation	764.5355006
Coefficient of variation (CV)	0.3972525407
Kurtosis	10.32736574
Mean	1924.557862
Median Absolute Deviation (MAD)	372
Skewness	1.833052855
Sum	3610470.55
Variance	584514.5316
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1650	37	1.0%
1950	37	1.0%
2000	25	0.7%
1578	25	0.7%
1640	22	0.6%
2150	22	0.6%
1900	19	0.5%
2408	19	0.5%
1930	18	0.5%
2812	17	0.5%
Other values (583)	1635	44.6%
(Missing)	1788	48.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
89	1	< 0.1%
145	1	< 0.1%
161	1	< 0.1%
215	1	< 0.1%
216	1	< 0.1%
325	1	< 0.1%
340	1	< 0.1%
352	1	< 0.1%
380	1	< 0.1%
406	1	< 0.1%

Value	Count	Frequency (%)
10000	1	< 0.1%
6926	1	< 0.1%
6000	1	< 0.1%
5800	2	0.1%
5514	1	< 0.1%
5350	2	0.1%
5200	2	0.1%
4890	1	< 0.1%
4857	1	< 0.1%
4848	2	0.1%

built_up_area
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
SKEWED

Distinct	641
Distinct (%)	38.2%
Missing	1988
Missing (%)	54.3%
Infinite	0
Infinite (%)	0.0%
Mean	2385.206461

Minimum	2
Maximum	737147
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	57.2 KiB

Quantile statistics

Minimum	2
5-th percentile	240.75
Q1	1113.5
median	1650
Q3	2400
95-th percentile	4657.5
Maximum	737147
Range	737145
Interquartile range (IQR)	1286.5

Descriptive statistics

Standard deviation	18016.18433
Coefficient of variation (CV)	7.553301828
Kurtosis	1654.580198
Mean	2385.206461
Median Absolute Deviation (MAD)	605
Skewness	40.54726143
Sum	3997606.029
Variance	324582897.6
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1800	41	1.1%
3240	37	1.0%
1900	34	0.9%
1350	33	0.9%
2700	32	0.9%
900	28	0.8%
1600	26	0.7%
1300	24	0.7%
2000	24	0.7%
1700	23	0.6%
Other values (631)	1374	37.5%
(Missing)	1988	54.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2	1	< 0.1%
14	1	< 0.1%
30	1	< 0.1%
33	1	< 0.1%
50	3	0.1%
53	1	< 0.1%
55	1	< 0.1%
56	1	< 0.1%
57	1	< 0.1%
60	5	0.1%

Value	Count	Frequency (%)
737147	1	< 0.1%
13500	1	< 0.1%
11286	1	< 0.1%
9500	1	< 0.1%
9000	7	0.2%
8775	1	< 0.1%
8286	1	< 0.1%
8067.8	1	< 0.1%
8000	1	< 0.1%
7500	2	0.1%

carpet_area
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
SKEWED

Distinct	731
Distinct (%)	39.1%
Missing	1793
Missing (%)	48.9%
Infinite	0
Infinite (%)	0.0%
Mean	2531.753542

Minimum	15
Maximum	607936
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	57.2 KiB

Quantile statistics

Minimum	15
5-th percentile	350
Q1	845
median	1300
Q3	1790.5
95-th percentile	2950
Maximum	607936
Range	607921
Interquartile range (IQR)	945.5

Descriptive statistics

Standard deviation	22805.78717
Coefficient of variation (CV)	9.007901754
Kurtosis	604.2183606
Mean	2531.753542
Median Absolute Deviation (MAD)	470
Skewness	24.32687466
Sum	4736910.877
Variance	520103928.6
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1400	42	1.1%
1800	35	1.0%
1600	35	1.0%
1200	31	0.8%
1500	29	0.8%
1650	28	0.8%
1350	27	0.7%
1300	23	0.6%
1450	22	0.6%
1000	22	0.6%
Other values (721)	1577	43.0%
(Missing)	1793	48.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
15	1	< 0.1%
33	1	< 0.1%
48	1	< 0.1%
50	1	< 0.1%
59	1	< 0.1%
60	1	< 0.1%
66	1	< 0.1%
72	1	< 0.1%
76.44	3	0.1%
77.31	1	< 0.1%

Value	Count	Frequency (%)
607936	1	< 0.1%
569243	1	< 0.1%
514396	1	< 0.1%
64529	1	< 0.1%
64412	1	< 0.1%
58141	1	< 0.1%
54917	1	< 0.1%
48811	1	< 0.1%
45966	1	< 0.1%
34401	1	< 0.1%

study room
Categorical

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	236.2 KiB

0	2967
1	697

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
0	2967	81.0%
1	697	19.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	2967	81.0%
1	697	19.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

servant room
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	236.2 KiB

0	2345
1	1319

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	2345	64.0%
1	1319	36.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	2345	64.0%
1	1319	36.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

store room
Categorical

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	236.2 KiB

0	3329
1	335

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	3329	90.9%
1	335	9.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	3329	90.9%
1	335	9.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

pooja room
Categorical

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	236.2 KiB

0	3014
1	650

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	3014	82.3%
1	650	17.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	3014	82.3%
1	650	17.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

others
Categorical

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	236.2 KiB

0	3262
1	402

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	3262	89.0%
1	402	11.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	3262	89.0%
1	402	11.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

furnishing_type
Categorical

Distinct	3
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	236.2 KiB

1	2406
0	1051
2	207

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	0
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	2406	65.7%
0	1051	28.7%
2	207	5.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	2406	65.7%
0	1051	28.7%
2	207	5.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

luxury_score
Real number (ℝ_≥0)

MISSING
ZEROS

Distinct	161
Distinct (%)	4.5%
Missing	121
Missing (%)	3.3%
Infinite	0
Infinite (%)	0.0%
Mean	72.39204064

Minimum	0
Maximum	174
Zeros	429
Zeros (%)	11.7%
Negative	0
Negative (%)	0.0%
Memory size	57.2 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	33
median	60
Q3	111
95-th percentile	174
Maximum	174
Range	174
Interquartile range (IQR)	78

Descriptive statistics

Standard deviation	53.26317381
Coefficient of variation (CV)	0.7357600828
Kurtosis	-0.9100305762
Mean	72.39204064
Median Absolute Deviation (MAD)	39
Skewness	0.4418276154
Sum	256485
Variance	2836.965685
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	429	11.7%
49	341	9.3%
174	194	5.3%
165	55	1.5%
38	54	1.5%
44	52	1.4%
72	51	1.4%
60	46	1.3%
37	44	1.2%
15	41	1.1%
Other values (151)	2236	61.0%
(Missing)	121	3.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	429	11.7%
5	6	0.2%
6	6	0.2%
7	41	1.1%
8	29	0.8%
9	9	0.2%
12	6	0.2%
13	10	0.3%
14	12	0.3%
15	41	1.1%

Value	Count	Frequency (%)
174	194	5.3%
169	1	< 0.1%
168	9	0.2%
167	21	0.6%
166	10	0.3%
165	55	1.5%
161	3	0.1%
160	27	0.7%
159	23	0.6%
158	33	0.9%

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Count
Heatmap

A simple visualization of nullity by column.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

First rows

	property_type	society	sector	price	price_per_sqft	area	areaWithType	bedRoom	bathroom	balcony	floorNum	facing	agePossession	super_built_up_area	built_up_area	carpet_area	study room	servant room	furnishing_type	luxury_score
0	flat	maa bhagwati residency	sector 7	0.45	5000.0	900.0	Carpet area: 900 (83.61 sq.m.)	2	2	1	4.0	West	Relatively New	NaN	NaN	900.0	0	0	1	28.0
1	flat	apna enclave	sector 3	0.50	7692.0	650.0	Carpet area: 650 (60.39 sq.m.)	2	2	1	1.0	West	Old Property	NaN	NaN	650.0	0	0	0	37.0
2	flat	tulsiani easy in homes	sohna road	0.40	6722.0	595.0	Carpet area: 595 (55.28 sq.m.)	2	2	3	12.0	NaN	New Property	NaN	NaN	595.0	0	0	1	36.0
3	flat	smart world orchard	sector 61	1.47	12250.0	1200.0	Carpet area: 1200 (111.48 sq.m.)	2	2	2	2.0	NaN	Undefined	NaN	NaN	1200.0	1	0	1	76.0
4	flat	parkwood westend	sector 92	0.70	5204.0	1345.0	Super Built up area 1345(124.95 sq.m.)	2	2	3	5.0	NaN	Under Construction	1345.0	NaN	NaN	1	0	1	0.0
5	flat	signature global infinity mall	sector 36	0.41	6269.0	654.0	Built Up area: 654 (60.76 sq.m.)	2	2	3	3.0	NaN	Undefined	NaN	654.0	NaN	0	0	1	0.0
6	flat	the cocoon	dwarka expressway	2.00	13333.0	1500.0	Super Built up area 1500(139.35 sq.m.)	3	3	3	5.0	NaN	New Property	1500.0	NaN	NaN	0	0	1	0.0
7	flat	ats triumph	sector 104	1.80	7860.0	2290.0	Carpet area: 2290 (212.75 sq.m.)	3	4	3	14.0	NaN	New Property	NaN	NaN	2290.0	0	0	1	60.0
8	flat	vatika xpressions	sector 88b	1.10	8148.0	1350.0	Built Up area: 1350 (125.42 sq.m.)Carpet area: 1050 sq.ft. (97.55 sq.m.)	2	4	3+	2.0	North-East	Under Construction	NaN	1350.0	1050.0	1	0	1	58.0
9	flat	raheja revanta	sector 78	4.75	16885.0	2813.0	Built Up area: 2813 (261.34 sq.m.)	3	3	2	31.0	NaN	Undefined	NaN	2813.0	NaN	0	1	1	100.0

Last rows

	property_type	society	sector	price	price_per_sqft	area	areaWithType	bedRoom	bathroom	balcony	floorNum	facing	agePossession	super_built_up_area	built_up_area	carpet_area	study room	servant room	store room	pooja room	furnishing_type	luxury_score
3654	house	independent	sector 31	3.50	24155.0	1449.0	Plot area 161(134.62 sq.m.)	4	3	3	2.0	South-West	Moderately Old	NaN	1449.0	NaN	0	0	1	0	0	NaN
3655	house	independent	sector 46	5.65	23870.0	2367.0	Plot area 263(219.9 sq.m.)	8	6	3+	3.0	South-West	Moderately Old	NaN	2367.0	NaN	0	1	0	0	0	NaN
3656	house	independent	sector 46	3.55	24500.0	1449.0	Plot area 161(134.62 sq.m.)	5	4	3+	3.0	North-West	Moderately Old	NaN	1449.0	NaN	0	1	0	0	0	NaN
3657	house	independent	sector 46	3.60	24845.0	1449.0	Plot area 161(134.62 sq.m.)	5	5	3+	3.0	South-East	Moderately Old	NaN	1449.0	NaN	0	1	0	0	0	NaN
3658	house	independent	sector 55	3.10	20026.0	1548.0	Plot area 172(143.81 sq.m.)	5	4	3+	2.0	North-East	Moderately Old	NaN	1548.0	NaN	0	1	1	0	0	NaN
3659	house	independent	sector 57	4.75	28787.0	1650.0	Plot area 1600(148.64 sq.m.)Built Up area: 1700 sq.ft. (157.94 sq.m.)Carpet area: 1650 sq.ft. (153.29 sq.m.)	3	3	3	2.0	North-West	Moderately Old	NaN	1700.0	1650.0	0	0	1	0	0	NaN
3660	house	dlf city phase 1	sector 26	5.50	30556.0	1800.0	Plot area 200(167.23 sq.m.)	4	4	3	2.0	North-East	Moderately Old	NaN	1800.0	NaN	1	1	0	1	1	NaN
3661	house	dlf city plots phase 2	sector 25	4.25	31481.0	1350.0	Plot area 150(125.42 sq.m.)	3	2	3	2.0	North	Old Property	NaN	1350.0	NaN	1	0	0	0	1	NaN
3662	house	dlf city phase 1	sector 26	4.50	33333.0	1350.0	Plot area 150(125.42 sq.m.)	3	3	2	2.0	East	Moderately Old	NaN	1350.0	NaN	1	1	0	0	1	NaN
3663	house	dlf city phase 1	sector 26	3.25	33129.0	981.0	Plot area 109(91.14 sq.m.)	3	3	3	2.0	West	Old Property	NaN	981.0	NaN	1	0	0	0	1	NaN

Overview

Variables

Common Values

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Pie chart

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Most frequent character per script

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Most frequent character per block

Common Values

Length

Most occurring characters

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Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values